regress help requested

I have a dataset in which all the dependent variables are for the years 2020 & 2021. I have 4 dependent variables, which are used in 4 different regressions. The independent variables are for the years 2018, 2019, 2020 & 2021.

Here is a sample of the dependent variables:

Code:

* Example generated by -dataex-. For more info, type help dataex
clear
input int year float(raw_return_ AbRet) double Vol1Yr_ float idio_volatility
2018         .         .       . .023706943
2019         .         .       . .023706943
2020         .         . 36.2264 .023706943
2021 -.3217149 -9.685585 28.7132 .023706943
2018         .         .       . .023706943
2019         .         .       . .023706943
2020         .         . 36.2264 .023706943
2021 -.3217149 -9.685585 28.7132 .023706943
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
2018         .         .       . .017640421
2019         .         .       . .017640421
2020  .0612004 -20.10798 28.3259 .017640421
2021         .         . 11.9041 .017640421
end

I have a plenty of independent variables. Here is a sample:

input int year byte(ESGScrFY ENVScrFY SocialScrFY GOVScrFY) float(size ROE profitability cash_over_assets stdebt_over_assets mtb) byte neg_mtb float HistVolatility
2018 13 0 4 26 6.073982 .021759655 .3056392 .3541455 .12199316 13.067905 0 1040.8689
2019 16 0 2 28 6.235095 .02212184 .2627229 .2828731 .09094698 12.02771 0 1040.8689
2020 20 0 8 32 6.534146 .023738274 .28146 .3461379 .1122328 13.204992 0 1040.8689
2021 24 16 17 31 6.548369 .01363123 .22036627 .3311015 .10458087 18.168388 0 1040.8689
2018 13 0 4 26 6.073982 .021759655 .3056392 .3541455 .12199316 13.067905 0 1040.8689
2019 16 0 2 28 6.235095 .02212184 .2627229 .2828731 .09094698 12.02771 0 1040.8689
2020 20 0 8 32 6.534146 .023738274 .28146 .3461379 .1122328 13.204992 0 1040.8689
2021 24 16 17 31 6.548369 .01363123 .22036627 .3311015 .10458087 18.168388 0 1040.8689
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 .
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 .
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 .
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 .
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 .
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 .
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 .
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 .
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 .
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 .
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 .
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 .
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 .
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 .
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 .
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 .
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 .
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 .
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 .
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 .
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 199.5806
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 199.5806
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 199.5806
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 199.5806
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 199.5806
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 199.5806
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 199.5806
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 199.5806
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 199.5806
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 199.5806
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 199.5806
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 199.5806
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 198.37877
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 198.37877
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 198.37877
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 198.37877
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 198.37877
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 198.37877
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 198.37877
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 198.37877
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 198.37877
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 198.37877
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 198.37877
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 198.37877
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 198.37877
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 198.37877
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 198.37877
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 198.37877
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 198.37877
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 198.37877
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 198.37877
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 198.37877
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 180.287
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 180.287
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 180.287
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 180.287
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 180.287
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 180.287
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 180.287
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 180.287
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 180.287
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 180.287
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 180.287
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 180.287
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 180.287
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 180.287
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 180.287
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 180.287
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 180.287
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 180.287
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 180.287
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 180.287
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 170.62106
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 170.62106
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 170.62106
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 170.62106
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 170.62106
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 170.62106
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 170.62106
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 170.62106
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 170.62106
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 170.62106
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 170.62106
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 170.62106
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 170.62106
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 170.62106
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 170.62106
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 170.62106
2018 76 83 73 75 9.837869 .08979048 .0126145 .020834863 .8490396 1.8775734 0 170.62106
2019 75 86 78 71 9.90103 .09026607 .011974652 .016592776 .8493556 1.830828 0 170.62106
2020 78 91 75 77 9.893396 .09819403 .009640835 .07133553 .8490928 1.442319 0 170.62106
2021 77 89 74 76 10.083617 .09861282 .012845165 .065547965 .8628278 1.7681098 0 170.62106
end
[/CODE]

I want to perform a regress where the dependent variable is from 2020 & 2021, but the independent variables are from 2018 & 2019. The following command gives me an error, since the dependent variables do not exist for those years.

regress raw_return_ ESGScrFY ENVScrFY SocialScrFY GOVScrFY size ROE profitability cash_over_assets stdebt_over_assets mtb neg_mtb HistVolatility if year==2018|year==2019, vce(cluster num_CIQ_ID)
no observations
r(2000);

How can I perform this regression where my dependent variable is from 2020 & 2021 and my independent variables are from 2018 & 2019. I would be very grateful for some advice.

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